Detection network self-discovery

ABSTRACT

Systems and methods for detecting the presence of a body in a network without fiducial elements, using signal absorption, and signal forward and reflected backscatter of radio frequency (RF) waves caused by the presence of a biological mass in a communications network.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is Continuation of U.S. Utility patent application Ser.No. 15/874,657, filed Jan. 18, 2018, which is a Continuation-In-Part ofU.S. Utility patent application Ser. No. 15/674,328, filed Aug. 10,2017, which is a Continuation-In-Part of U.S. Utility patent applicationSer. No. 15/600,380, filed May 19, 2017, which is a Continuation of U.S.Utility patent application Ser. No. 15/227,717, filed Aug. 3, 2016, andissued on Jun. 27, 2017, as U.S. Pat. No. 9,693,195, which claims thebenefit of U.S. Provisional Patent Application No. 62/252,954, filedNov. 9, 2015, and U.S. Provisional Patent Application No. 62/219,457,filed Sep. 16, 2015 and which is a continuation of U.S. Utility patentapplication Ser. No. 15/084,002, filed Mar. 29, 2016, and issued on Oct.18, 2016, as U.S. Pat. No. 9,474,042, which application in turn alsoclaims benefit of U.S. Provisional Patent Application No. 62/252,954,filed Nov. 9, 2015, and U.S. Provisional Patent Application No.62/219,457, filed Sep. 16, 2015. The entire disclosure of all of thesedocuments is herein incorporated by reference.

BACKGROUND 1. Field of the Invention

This disclosure is related to the field of object detection, and moreparticularly to systems and methods for detecting the presence of abiological mass within a wireless communications network.

2. Description of the Related Art

Tracking objects may be done using a number of techniques. For example,a moving transceiver may be attached to the object. Examples of suchsystems include global positioning location systems such as GPS, whichuse orbiting satellites to communicate with terrestrial transceivers.However, such systems are generally less effective indoors, wheresatellite signals may be blocked, reducing accuracy. Thus, othertechnologies are often used indoors, such as Bluetooth™ beacons, whichcalculate the location of a roaming or unknown transceiver. The roamingtransceiver acts as a fiducial element.

These systems have several disadvantages, among them that the objecttracked must include a transceiver. In certain applications, the objectto be tracked will have no such fiducial element, or will activelydisable any such element, such as an intruder in a home.

Other technologies exist which can also detect and track objects withoutthe use of a fiducial element. For example, radar is a venerableobject-detection system that uses RF waves to determine the range,angle, or velocity of objects, including aircraft, ships, spacecraft,guided missiles, motor vehicles, weather formations, and terrain. Radaroperates by transmitting electromagnetic waves, generally using waves inthe radio frequency (“RF”) of the electromagnetic spectrum, whichreflect from any object in their path. A receiver, typically part of thesame system as the transmitter, receives and processes these reflectedwaves to determine properties of the objects. Other systems similar toradar, using other parts of the electromagnetic spectrum, may also beused in similar fashion, such as ultraviolet, visible, or near-infraredlight from lasers.

Radar technologies do not require a fiducial element, but have othershortcomings. For example, radar signals are susceptible to signalnoise, or random variations in the signal caused by internal electricalcomponents, as well as noise and interference from external sources,such as the natural background radiation. Radar is also vulnerable toexternal interference sources, such as intervening objects blocking thebeam path and can be deceived by objects of particular size, shape, andorientation.

In addition, the growth of home automation technologies has provided awealth of additional interaction vectors for “Internet of Things”(“IoT”) devices, including voice recognition for voice-based control.This technology has been proliferated by various commercial enterprisessuch as Amazon (Alexa), Google (Google Home), Apple (Siri), andMicrosoft (Cortana). These voice recognition systems are currently usedwith IOT devices to provide users with the ability to provide spokenword input to IOT devices, instructing them to perform certainfunctions. Currently, this interaction is typically one-directional,with the voice control system sending commands to the IoT device andreceiving status updates from those devices when queried by the voicecontrol system. The market lacks third-party systems which trigger voicerecognition systems, such as to prompt a response.

SUMMARY

The following is a summary of the invention in order to provide a basicunderstanding of some aspects of the invention. This summary is notintended to identify key or critical elements of the invention or todelineate the scope of the invention. The sole purpose of this sectionis to present some concepts of the invention in a simplified form as aprelude to the more detailed description that is presented later.

Because of these and other problems in the art, there is describedherein, among other things, is a method for detecting the presence of ahuman comprising: providing a first transceiver disposed at a firstposition within a detection area; providing a second transceiverdisposed at a second location within the detection area; a computerserver communicably coupled to the first transceiver; the firsttransceiver receiving a first set of wireless signals from the secondtransceiver via the wireless communications network; the computer serverreceiving a first set of signal data from the first transceiver, thefirst set of signal data comprising data about the properties of thefirst set of wireless signals, the property data being generated as partof ordinary operation of the first transceiver on the communicationnetwork; the computer server creating a baseline signal profile forcommunications from the second transceiver to the first transceiver, thebaseline signal profile being based at least in part on the wirelesssignal properties in the received first set of signal data, andrepresenting characteristics of wireless transmissions from the secondtransceiver to the first transceiver when no human is present in thedetection area; the first transceiver receiving a second set of wirelesssignals from the second transceiver via the wireless communicationsnetwork; the computer server receiving a second set of signal data fromthe first transceiver, the second set of signal data comprising dataabout the properties of the second set of wireless signals, the propertydata being generated as part of ordinary operation of the firsttransceiver on the communication network; and the computer serverdetermining whether a human is present within the detection area, thedetermination based at least in part on a comparison of the wirelesssignal properties in the received second set of wireless signal data tothe baseline signal profile.

In an embodiment of the method, the first set of signal propertiescomprise wireless network signal protocol properties determined by thefirst transceiver.

In another embodiment of the method, the wireless network signalprotocol properties are selected from the group consisting of: receivedsignal strength, latency, and bit error rate.

In another embodiment of the method, the method further comprises:providing a third transceiver disposed at a third location within thedetection area; the first transceiver receiving a third set of wirelesssignals from the third transceiver via the wireless communicationsnetwork; the computer server receiving a third set of signal data fromthe first transceiver, the third set of signal data comprising dataabout the properties of the third set of wireless signals, the propertydata being generated as part of ordinary operation of the firsttransceiver on the communication network; the computer server creating asecond baseline signal profile for communications from the thirdtransceiver to the first transceiver, the second baseline signal profilebeing based at least in part on the wireless signal properties in thereceived third set of signal data, and representing characteristics ofwireless transmissions from the third transceiver to the firsttransceiver when no human is present in the detection area; the firsttransceiver receiving a fourth set of wireless signals from the thirdtransceiver via the wireless communications network; the computer serverreceiving a fourth set of signal data from the first transceiver, thefourth set of signal data comprising data about the properties of thefourth set of wireless signals, the property data being generated aspart of ordinary operation of the first transceiver on the communicationnetwork; and in the determining step, the computer server determiningwhether a human is present within the detection area based at least inpart on a comparison of the wireless signal properties in the receivedfourth set of wireless signal data to the second baseline signalprofile.

In another embodiment of the method, the determining step appliesstatistical methods to the second set of wireless signal data todetermine the presence of a human.

In another embodiment of the method, the method further comprises: thecomputer server continuously determining the presence or absence of ahuman within the detection area, the determination based at least inpart on a comparison of the baseline signal profile to signal datacomprising data about the properties of the first set of wirelesssignals received continuously at the computer server from the firsttransceiver; and the computer continuously updating the baseline signalprofile based on the continuously received signal data when thecontinuously received signal data indicates the absence of a human inthe detection area.

In another embodiment of the method, the method further comprises: thecomputer server determining the number of humans present within thedetection area, the determination based at least in part on a comparisonof the received second set of signal properties to the baseline signalprofile.

In another embodiment of the method, the method further comprises: thecomputer server determining the location of one or more humans withinthe detection area, the determination based at least in part on acomparison of the received second set of signal properties to thebaseline signal profile.

In another embodiment of the method, the method further comprises: thecomputer server being operatively coupled to a second system; and onlyafter the computer server detects the presence of a human in thedetection area, the computer operates the second system.

In another embodiment of the method, the detection network and thesecond system are configured to communicate using the same communicationprotocol.

In another embodiment of the method, the second system is an electricalsystem.

In another embodiment of the method, the second system is a lightingsystem.

In another embodiment of the method, the second system is a heating,venting, and cooling (HVAC) system.

In another embodiment of the method, the second system is a securitysystem.

In another embodiment of the method, the second system is an industrialautomation system.

In another embodiment of the method, the wireless communication protocolis selected from the group consisting of: Bluetooth™, Bluetooth™ LowEnergy, ANT, ANT+, WiFi, Zigbee, Thread, and Z-Wave.

In another embodiment of the method, the wireless communication networkhas a carrier frequency in the range of 850 MHz and 17.5 GHz inclusive.

In another embodiment of the method, the determination whether a humanis present within the detection area is adjusted based on machinelearning comprising: determining a first sample location of a humanhaving a fiducial element in the detection area, the first samplelocation being determined based upon detecting the fiducial element;determining a second sample location of the human in the detection area,the second sample location being determined based at least in part on acomparison of the received second set of signal data to the baselinesignal profile not utilizing the fiducial element; comparing the firstsample location and the second sample location; and adjusting thedetermination step based on non-fiducial element location to improve thelocation calculating capabilities of the system, the adjusting basedupon the comparing step.

In another embodiment of the method, the determination whether a humanis present within the detection area is adjusted based on machinelearning comprising: determining based on user input or action that ahuman was present in an area when the sample signal propertiescorrespond at least in part with baseline signal properties of an emptyspace, modifying, at least in part, the baseline signal properties foran empty space; modifying, at least in part, the signal propertiesassociated with an occupied space; and adjusting the method forcomparing sample signal properties to the baseline and other comparativesignal properties to improve the accuracy of the system over time.

In an embodiment of the system, the user input or action which providespresence data is provided directly to the system in some form including,but not limited to, physical switches, smartphone input, or auditorycues.

In an embodiment of the system, the user input or action which providespresence data is provided indirectly to the system in some form, such asdeliberately changing the signal profile to counteract a decision beingtaken by the system, such as providing such a change during a dimmingphase in a lighting system.

In another embodiment of the method, the method further comprises: thecomputer server storing a plurality of historical data recordsindicative of whether a human was present in the detection area over aperiod of time, each of the historical data records comprising anindication of the number of humans detected in the detected area and thedate and time of when the number of humans was detected in the detectionarea; and the computer server making the historical data recordsavailable to one or more external computer systems via an interface.

Also described herein, among other things, is a method for detecting thepresence of a human comprising: providing a first transceiver disposedat a first position within a detection area; providing a secondtransceiver disposed at a second location within the detection area;providing a computer server communicably coupled to the firsttransceiver; providing a first external system operatively coupled tothe computer server; providing a second external system operativelycoupled to the computer server; the computer server receiving from thefirst transceiver a set of baseline signal data comprising property dataabout the signal properties of a first set of wireless signals receivedby the first transceiver from the second transceiver when no human ispresent in the detection area, the property data being generated by thefirst transceiver as part of ordinary operation of the first transceiveron the communication network; the computer server creating a baselinesignal profile for communications from the second transceiver to thefirst transceiver when no human is present in the detection area, thebaseline signal profile being based at least in part on the propertydata representing characteristics of wireless transmissions from thesecond transceiver to the first transceiver when no human is present inthe detection area; the computer server receiving from the firsttransceiver a first set of sample baseline signal data comprisingproperty data about the signal properties of a second set of wirelesssignals received by the first transceiver from the second transceiverwhen a human is present in the detection area, the property data beinggenerated by the first transceiver as part of ordinary operation of thefirst transceiver on the communication network; the computer servercreating a first sample baseline signal profile for communications fromthe second transceiver to the first transceiver when a human is presentin the detection area, the first sample baseline signal profile beingbased at least in part on the property data in the first set of samplebaseline signal data, representing characteristics of wirelesstransmissions from the second transceiver to the first transceiver whena human is present in the detection area; the computer server receivingfrom the first transceiver a second set of sample baseline signal datacomprising property data about the signal properties of a third set ofwireless signals received by the first transceiver from the secondtransceiver when a human is present in the detection area, the propertydata being generated by the first transceiver as part of ordinaryoperation of the first transceiver on the communication network; thecomputer server creating a second sample baseline signal profile forcommunications from the second transceiver to the first transceiver whena human is present in the detection area, the second sample baselinesignal profile being based at least in part on the property data in thesecond set of sample baseline signal data, representing characteristicsof wireless transmissions from the second transceiver to the firsttransceiver when a human is present in the detection area; the computerserver receiving from the first transceiver a third set of samplebaseline signal data comprising property data about the signalproperties of a fourth set of wireless signals received by the firsttransceiver from the second transceiver when a human is present in thedetection area, the property data being generated by the firsttransceiver as part of ordinary operation of the first transceiver onthe communication network; the computer server determining to operatethe first external system based upon the computer server determiningthat the property data in the third set of sample baseline signal datacorresponds to the first sample baseline signal profile; the computerserver determining not to operate the second external system based uponthe computer server determining that the property data in the third setof sample baseline signal data does not correspond to the second samplebaseline signal profile.

In an embodiment of the method, the determination to operate the firstexternal system and the determination not to operate the second externalsystem is adjusted based on machine learning comprising: determining afirst sample location of a human having a fiducial element in thedetection area, the first sample location being determined based upondetecting the fiducial element; determining a second sample location ofthe human in the detection area, the second sample location beingdetermined based at least in part on a comparison of the received secondset of signal data to the baseline signal profile not utilizing thefiducial element; comparing the first sample location and the secondsample location; and adjusting the determination steps based onnon-fiducial element location to improve the location calculatingcapabilities of the system, the adjusting based upon the comparing step.

In another embodiment of the method, the determination to operate thefirst external system and the determination not to operate the secondexternal system is adjusted based on machine learning comprising:determining a first sample location of a human in the detection areausing inference, the first sample location being determined based upondetecting the human interacting with the system in some known way;determining a second sample location of the human in the detection area,the second sample location being determined based at least in part on acomparison of the received second set of signal data to the baselinesignal profile not utilizing the inferred location; comparing the firstsample location and the second sample location; and adjusting thedetermination steps based on inferred location to improve the locationcalculating capabilities of the system, the adjusting based upon thecomparing step.

In another embodiment of the method, the property data about thewireless signals comprises data about signal properties selected fromthe group consisting of: received signal strength, latency, and biterror rate.

In another embodiment of the method, the computer server creates thefirst sample baseline signal profile by applying statistical methods tothe first set of sample baseline signal data, and the computer servercreates the second sample baseline signal profile by applyingstatistical methods to the second set of sample baseline signal data.

In another embodiment of the method, the method further comprises: thecomputer server receiving from the first transceiver additional sets ofbaseline signal data comprising property data about the signalproperties of a second set of wireless signals received by the firsttransceiver from the second transceiver, the property data beinggenerated by the first transceiver as part of ordinary operation of thefirst transceiver on the communication network and the computer serverupdating the baseline signal profile based on the continuously receivedadditional sets of baseline signal data when the continuously receivedsets of baseline signal data indicate the absence of a human in thedetection area.

In another embodiment of the method, the method further comprises: thecomputer server receiving from the first transceiver a set of signaldata comprising property data about the signal properties of a secondset of wireless signals received by the first transceiver from thesecond transceiver when one or more humans are present in the detectionarea, the property data being generated by the first transceiver as partof ordinary operation of the first transceiver on the communicationnetwork; the computer server determining the quantity of humans presentin the detection area based at least in part on a comparison of the setof signal data to the baseline signal profile.

In another embodiment of the method, the method further comprises: thecomputer server determining a location of each of the one or more humanspresent in the detection area, the determination based at least in parton a comparison of the set of signal data to the baseline signalprofile.

In another embodiment of the method, when a human is present in thedetection area, the computer server determines that a human is presentin the detection area and operates the first external system even if theproperty data in the third set of sample baseline signal datacorresponds to the second sample baseline signal profile.

In another embodiment of the method, when a human is present in thedetection area, the computer server determines that a human is presentin the detection area and operates the second external system only ifthe property data in the third set of sample baseline signal datacorresponds to the second sample baseline signal profile.

In another embodiment of the method, the wireless communication networkhas a carrier frequency in the range of 850 MHz and 17.5 GHz inclusive.

In another embodiment of the method, the method further comprises: thecomputer server storing a plurality of historical data recordsindicative of whether a human was present in the detection area over aperiod of time, each of the historical data records comprising anindication of the number of humans detected in the detected area and thedate and time of when the number of humans was detected in the detectionarea; and the computer server making the historical data recordsavailable to one or more external computer systems via an interface.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of an embodiment of a system according tothe present disclosure.

FIG. 2 is a flowchart of an embodiment of a method according to thepresent disclosure.

FIG. 3A depicts a schematic diagram of a system for change detection ina detection network over time according to the present disclosure.

FIG. 3B depicts a schematic diagram of a system for detecting changes inlocations of humans in a detection network over time according to thepresent disclosure.

FIG. 4 depicts a schematic diagram of a system for forming an ad hocnetwork according to the present disclosure.

FIG. 5 depicts an alternative embodiment of a system for forming an adhoc network according to the present disclosure.

FIG. 6 depicts a flowchart of an embodiment of a method for forming anad hoc disclosure according to the present disclosure.

FIG. 7 depicts an alternative embodiment of a system and method forforming an ad hoc network according to the present disclosure.

DESCRIPTION OF THE PREFERRED EMBODIMENT(S)

The following detailed description and disclosure illustrates by way ofexample and not by way of limitation. This description will clearlyenable one skilled in the art to make and use the disclosed systems andmethods, and describes several embodiments, adaptations, variations,alternatives and uses of the disclosed systems and methods. As variouschanges could be made in the above constructions without departing fromthe scope of the disclosures, it is intended that all matters containedin the description or shown in the accompanying drawings shall beinterpreted as illustrative and not in a limiting sense.

Generally speaking, described herein, among other things, are systemsand methods for detecting the presence of a body in a network withoutfiducial elements. Generally speaking, the systems and methods describedherein use signal absorption, and signal forward scatter and reflectedbackscatter of the RF communication caused by the presence of abiological mass in a communications network, generally a mesh network.Additionally, this disclosure describes various systems and methods forintegrating such presence sensing technology with other systems, such aselectrical, security, and industrial automation systems.

Throughout this disclosure, the term “computer” describes hardware whichgenerally implements functionality provided by digital computingtechnology, particularly computing functionality associated withmicroprocessors. The term “computer” is not intended to be limited toany specific type of computing device, but it is intended to beinclusive of all computational devices including, but not limited to:processing devices, microprocessors, personal computers, desktopcomputers, laptop computers, workstations, terminals, servers, clients,portable computers, handheld computers, smart phones, tablet computers,mobile devices, server farms, hardware appliances, minicomputers,mainframe computers, video game consoles, handheld video game products,and wearable computing devices including but not limited to eyewear,wrist-wear, pendants, and clip-on devices.

As used herein, a “computer” is necessarily an abstraction of thefunctionality provided by a single computer device outfitted with thehardware and accessories typical of computers in a particular role. Byway of example and not limitation, the term “computer” in reference to alaptop computer would be understood by one of ordinary skill in the artto include the functionality provided by pointer-based input devices,such as a mouse or track pad, whereas the term “computer” used inreference to an enterprise-class server would be understood by one ofordinary skill in the art to include the functionality provided byredundant systems, such as RAID drives and dual power supplies.

It is also well known to those of ordinary skill in the art that thefunctionality of a single computer may be distributed across a number ofindividual machines. This distribution may be functional, as wherespecific machines perform specific tasks; or, balanced, as where eachmachine is capable of performing most or all functions of any othermachine and is assigned tasks based on its available resources at apoint in time. Thus, the term “computer” as used herein, can refer to asingle, standalone, self-contained device or to a plurality of machinesworking together or independently, including without limitation: anetwork server farm, “cloud” computing system, software-as-a-service, orother distributed or collaborative computer networks.

Those of ordinary skill in the art also appreciate that some deviceswhich are not conventionally thought of as “computers” neverthelessexhibit the characteristics of a “computer” in certain contexts. Wheresuch a device is performing the functions of a “computer” as describedherein, the term “computer” includes such devices to that extent.Devices of this type include but are not limited to: network hardware,print servers, file servers, NAS and SAN, load balancers, and any otherhardware capable of interacting with the systems and methods describedherein in the matter of a conventional “computer.”

Throughout this disclosure, the term “software” refers to code objects,program logic, command structures, data structures and definitions,source code, executable and/or binary files, machine code, object code,compiled libraries, implementations, algorithms, libraries, or anyinstruction or set of instructions capable of being executed by acomputer processor, or capable of being converted into a form capable ofbeing executed by a computer processor, including without limitationvirtual processors, or by the use of run-time environments, virtualmachines, and/or interpreters. Those of ordinary skill in the artrecognize that software can be wired or embedded into hardware,including without limitation onto a microchip, and still be considered“software” within the meaning of this disclosure. For purposes of thisdisclosure, software includes without limitation: instructions stored orstorable in RAM, ROM, flash memory BIOS, CMOS, mother and daughter boardcircuitry, hardware controllers, USB controllers or hosts, peripheraldevices and controllers, video cards, audio controllers, network cards,Bluetooth™ and other wireless communication devices, virtual memory,storage devices and associated controllers, firmware, and devicedrivers. The systems and methods described herein are contemplated touse computers and computer software typically stored in a computer- ormachine-readable storage medium or memory.

Throughout this disclosure, terms used herein to describe or referencemedia-holding software, including without limitation terms such as“media,” “storage media,” and “memory,” may include or excludetransitory media such as signals and carrier waves.

Throughout this disclosure, the term “network” generally refers to avoice, data, or other telecommunications network over which computerscommunicate with each other. The term “server” generally refers to acomputer providing a service over a network, and a “client” generallyrefers to a computer accessing or using a service provided by a serverover a network. Those having ordinary skill in the art will appreciatethat the terms “server” and “client” may refer to hardware, software,and/or a combination of hardware and software, depending on context.Those having ordinary skill in the art will further appreciate that theterms “server” and “client” may refer to endpoints of a networkcommunication or network connection, including but not necessarilylimited to a network socket connection. Those having ordinary skill inthe art will further appreciate that a “server” may comprise a pluralityof software and/or hardware servers delivering a service or set ofservices. Those having ordinary skill in the art will further appreciatethat the term “host” may, in noun form, refer to an endpoint of anetwork communication or network (e.g., “a remote host”), or may, inverb form, refer to a server providing a service over a network (“hostsa website”), or an access point for a service over a network.

Throughout this disclosure, the term “real time” refers to softwareoperating within operational deadlines for a given event to commence orcomplete, or for a given module, software, or system to respond, andgenerally invokes that the response or performance time is, in ordinaryuser perception and considered the technological context, effectivelygenerally contemporaneous with a reference event. Those of ordinaryskill in the art understand that “real time” does not literally mean thesystem processes input and/or responds instantaneously, but rather thatthe system processes and/or responds rapidly enough that the processingor response time is within the general human perception of the passageof real time in the operational context of the program. Those ofordinary skill in the art understand that, where the operational contextis a graphical user interface, “real time” normally implies a responsetime of no more than one second of actual time, with milliseconds ormicroseconds being preferable. However, those of ordinary skill in theart also understand that, under other operational contexts, a systemoperating in “real time” may exhibit delays longer than one second,particularly where network operations are involved.

Throughout this disclosure, the term “transmitter” refers to equipment,or a set of equipment, having the hardware, circuitry, and/or softwareto generate and transmit electromagnetic waves carrying messages,signals, data, or other information. A transmitter may also comprise thecomponentry to receive electric signals containing such messages,signals, data, or other information, and convert them to suchelectromagnetic waves. The term “receiver” refers to equipment, or a setof equipment, having the hardware, circuitry, and/or software to receivesuch transmitted electromagnetic waves and convert them into signals,usually electrical, from which the message, signal, data, or otherinformation may be extracted. The term “transceiver” generally refers toa device or system that comprises both a transmitter and receiver, suchas, but not necessarily limited to, a two-way radio, or wirelessnetworking router or access point. For purposes of this disclosure, allthree terms should be understood as interchangeable unless otherwiseindicated; for example, the term “transmitter” should be understood toimply the presence of a receiver, and the term “receiver” should beunderstood to imply the presence of a transmitter.

Throughout this disclosure, the term “detection network” refers to awireless network used in the systems and methods of the presentdisclosure to detect the presence of biological mass interposed withinthe communications area of the network. A detection network may usegeneral networking protocols and standards and may be, but is notnecessarily, a special-purpose network. That is, while the nodes in thenetwork could be deployed for the specific purpose of setting up awireless detection network according to the present invention, they neednot be and generally will not be. Ordinary wireless networks establishedfor other purposes may be used to implement the systems and methodsdescribed herein. In the preferred embodiment, the detection networkuses a plurality of Bluetooth™ Low Energy nodes, but the presentdisclosure is not limited to such nodes. Each node acts as a computerwith an appropriate transmitter and receiver for communicating over thenetwork. Each of the computers provides a unique identifier within thenetwork whenever transmitting a message such that a receiving computeris capable of discerning from where the message originated. Such messageorigination information will usually be critical to the functioning ofthe invention as described in this detailed description. The receivingcomputer then analyzes the incoming signal properties, including but notlimited to, signal strength, bit error rate, and message delay. Thedetection network may be a mesh network, which means a network topologyin which each node relays data from the network.

Throughout this disclosure, the term “node” refers to a start point orendpoint for a network communication, generally a device having awireless transceiver and being a part of a detection network. Nodes aregenerally standalone, self-contained networking devices, such aswireless routers, wireless access points, short-range beacons, and soforth. A node may be a general-purpose device or a special-purposedevice configured for use in a detection network as described herein. Byway of example and not limitation, a node may be a device having thewireless transmission capabilities of an off-the-shelf wirelessnetworking device with the addition of specialized hardware, circuitry,componentry, or programming for implementing the systems and methodsdescribed herein; that is, for detecting significant changes to signalproperties, including but not limited to, signal strength, bit errorrate, and message delay. Within a detection network, each node can actas both a transmitter of signal to the network, as well as a receiverfor other nodes to push information. In the preferred embodiment, thenodes utilize Bluetooth™ Low Energy (BLE) as a wireless networkingsystem.

Throughout this disclosure, the term “continuous” refers to somethinghappening at an ongoing basis over time, whether such events aremathematically continuous or discontinuous. The generally acceptedmathematical definition of “continuous function” describes a functionwhich is without holes or jumps, generally described by two-sidedlimits. The technology described herein is based upon disturbances to atelecommunications system, in which the transceivers transmit atdiscrete intervals, and the received raw data is taken discretely, i.e.at discrete time intervals. The resulting data in itself may be discretein that it captures the characteristic of the system during a particularobservation window (i.e., the time interval). In a physical ormathematical sense, this mechanism is essentially a set of discrete datapoints in time, implying a discontinuous function. However, in thecontext of the technology, one of ordinary skill in the art wouldunderstand a system exhibiting this type of behavior to be “continuous”given that such measurements are taken at an ongoing basis over time.

This application should be understood with respect to the systems andmethods for detecting the presence of a human within a detectionnetwork, or “Network Presence Sensing” (NPS) described in U.S. Utilitypatent application Ser. No. 15/674,328, filed Aug. 10, 2017, U.S.Utility patent application Ser. No. 15/600,380, filed May 19, 2017, U.S.Pat. Nos. 9,693,195, 9,474,042, U.S. Provisional Patent Application No.62/252,954, filed Nov. 9, 2015, and U.S. Provisional Patent ApplicationNo. 62/219,457, filed Sep. 16, 2015. This disclosures of all of thesedocuments are incorporated herein by reference. Various aspects of thesedisclosures are discussed herein, including NPS, which is, at a highlevel, the inference of the presence of humans within a detectionnetwork based on changes in the characteristics of wireless networksignals caused by the absorption of wireless waves caused by the watermass of the human body within the detection network. FIG. 1 is aschematic diagram of a system and method for NPS according to the abovereferences. FIG. 2 depicts an embodiment (201) of a method for NPSaccording to the above references. FIGS. 3A and 3B depict embodiments ofNPS using change detection according to the above references.

The present disclosure is directed to systems and methods forrecognizing and including devices in a detection network on an ad hocbasis. This has the effect of such devices being part of both anindependent primary function network (e.g., the network functions forwhich the device is configured for use according to its intendedpurpose), as well as part of a secondary function network (meaning adetection network implementing NPS technology). The present systems andmethods facilitate a plurality of unrelated devices from differentmanufacturers, and having different primary functions, cooperating in asecondary function network in which they can share functionality.

FIGS. 4 and 5 depict an embodiment of a system according to the presentdisclosure before and after the formation of a secondary functionnetwork (501B). In FIG. 4, a primary function network (501A) is formedprimarily by a wireless router (503A). When a user (502) brings a userdevice (505) within the range of the primary function network (501A),the user device (505) joins the primary function network (501A), andthen form a secondary function network (501B) among certain devices.After the secondary function network (501B) is formed, as shown in thedepicted embodiment of FIG. 5, the devices form two generallyoverlapping networks (501A) and (501B), the first being the primaryfunction network (501A) which provides ordinary network communications,and the second (501B) being a secondary function network (501B)configured to provide NPS and functionality sharing. The secondarynetwork (501B) does not necessarily provide general purpose networking.These and other aspects are described in further detail elsewhereherein.

In the depicted embodiment, a primary function network (501A) is shownformed by a plurality of nodes (503A, 503B, 503C, and 503D). In thedepicted embodiment, node (503A) is a wireless router, node (503B) is asmart thermostat, node (505C) is a smart power receptacle, and node(503D) is a smart light controller. The special purpose nodes (503B),(503C) and (503D) communicate (511) directly or indirectly via therouter (503A), which also provides Internet connectivity (513). AlthoughFIGS. 4 and 5 depicts nodes in the form of routers, smart thermostats,smart light controllers, and smart power receptacles, it will beunderstood by a person of ordinary skill in the art that these areexemplary embodiments only, and that in a given embodiment, a node maybe any type of device configured for, and/or capable of being configuredfor, wireless communication as described in this disclosure.

The depicted nodes (503A), (503B), (503C) and (503D), and particularlythe depicted smart devices (503B), (503C), and (503D) may in turn be incommunication (wired or wireless) (515) with one or more other connecteddevices. These additional devices may or may not also communicate viathe router (503A). By way of example and not limitation, the depictedsmart thermostat (503B) directly communicates (515) with a sensor(503E), such as a fire alarm, smoke detector, carbon monoxide detector,radon detector, and the like. Likewise, the depicted smart lightcontroller (503D) directly communicates (515) with one or more smartlights (503F) installed in a light fixture in a structure.

As will be clear to one of ordinary skill in the art, each of thedepicted smart devices (503B), (503C), and (503D) is, or may be,developed and manufactured by a different company, resulting in eachsuch device (503B), (503C), and (503D) being designed and configured forwireless communication (515) with other devices in the same device“ecosystem.” For example, a smart thermostat (503B) is configured tocommunicate (515) with sensors (503E) configured to communicate with thesmart thermostat (503B). Thus, a consumer who purchases a Google Nest™smart thermostat will use it with other compatible products configuredto work with Google Nest™.

Generally, smart devices (503B), (503C), and (503D), such as thosedepicted in FIGS. 4 and 5, each communicate over wireless communicationprotocols defined by a standard, such as a protocol in the IEEE 802.11or 802.15 families of protocols, known commercially as WiFi, Bluetooth™,and Zigbee™. However, layered on top of these standard protocols areapplication-specific protocols, which are usually particular to eachfamily or “ecosystem” of related devices. Thus, the depicted smart light(503F), while compatible with the smart light controller (503D), is notnecessarily able to be directly controlled or operated by the depictedsmart thermostat (503B) or sensor (503E) manufactured by a differentcompany.

Regardless, because all of these devices are capable of transmittingover standard protocols, they can “see” each other within the primaryfunction network (501A), directly or indirectly (e.g., via the router(503A)). Thus, each device is generally discoverable by the otherdevices merely by the fact that each device is actively transmittingwireless signals via standard protocols, even though not all devices cannecessarily be functionally controlled or operated by any otherparticular device due to the use of proprietary protocols.

Additionally, the network (501A) may include within its range otherdevices, such as the wireless headphones (503G) depicted in FIGS. 4 and5, which do not communicate via the wireless router (503A), but arecapable of communicating using at least some of the same standardwireless protocols. These devices (503G), whether or not paired to orcommunicating with any other device, are generally discoverable by otherdevices within the network (501). For example, if a user (502) entersthe network (501A) holding a mobile phone (505), the mobile phone (505)generally will be able to detect the presence of the wireless router(503A), the smart thermostat (503B), the smart power receptacle (503C),the smart light controller (503D), and (if powered on) the wirelessheadphones (503G). The mobile phone (505) may additionally be able todetect the sensor (503E) and/or the smart light (503F).

The present systems and methods describe techniques and concepts forutilizing some or all of the wireless transmitters embedded in thesedevices (503A), (503B), (503C), (503D), (503E), (503F) and (503G)(collectively, “devices (503 n)”) to form and operate a secondaryfunction network (501B), which both facilitates the detection of humanswithin the physical range of the transmitters in the devices (503 n), aswell as allows for the aggregation of the various functions of eachseparate ecosystem into a single, unified system. This network can beformed as a planned network or as an ad hoc network.

By way of example and not limitation, in the depicted embodiment of FIG.4, if carbon monoxide is detected by sensor (503E), it may be desirableto operate the lights, such as by flashing on and off, to alertoccupants that a potentially dangerous condition is present. However,the smart thermostat (503B) may not be able to directly operate thesmart light (503F) in response to the sensor (503E) detecting carbonmonoxide, because the depicted smart light (503F) is only configured tointeract with the controller (503D).

These limitations are overcome using the systems and methods describedherein. At a high level, this is done by a first device (such as but notlimited to a mobile device (505)), which is configured for establishinga network presence sensing secondary function network (501B), forming asecondary function network (501B) amongst one or more other devices(such as but not limited to one or more of the depicted nodes (503 n)).These other devices then in turn may utilize still other devices thatthey connect to via proprietary protocols in their particular ecosystem.This allows for these other devices to be used in the NPS network (501B)without having to be configured specifically for this purpose.

Once the network of compatible devices for the secondary functionnetwork (501B) is discovered, their identities and functionalities canbe broadcast or otherwise communicated over the secondary (501B) (orprimary (501A)) function network, and these devices then may begin tocommunicate with each other in either, or both, a primary functionnetwork (501A) and/or a secondary function network (501B), as shown inFIG. 5. This may further comprise negotiating the use of the availablenetwork resources to facilitate NPS and other primary and/or secondarynetwork functions. Additionally, a central server (504) may be used tomanage participating devices, facilitating the aggregation of differentfunctions of differing device ecosystems into a single service tower.

An embodiment of a method for forming a secondary function network(501B), such as that depicted in FIG. 5, is depicted in FIG. 6. As such,the method depicted in FIG. 6 is described with respect to the systemdepicted in FIGS. 4-5. In the depicted embodiment of FIG. 6, an end-userdevice (505) is configured (701) for use as a node in a detectionnetwork (501B). Next, the configured device (505) is used to form orjoin (703) a detection network (501B). Next, the formed or joineddetection network (501B) provides NPS functionality (705). Finally, andoptionally, the configured device (505) at some point may exit (707), orthe detection network (501B) may be disbanded (707). These steps aredescribed in further detail herein.

There are a number of ways for a device (505) to be configured (701) foruse as a node in a detection network (501B). This configuration mayinclude configuring a device (505) with software, or hardware, fordiscovering other NPS-ready devices (503 n) within transmission range ofthe transmitter in the device (505), and for forming or joining (703) adetection network (501B) comprised of such discovered devices. Forexample, the device (505) firmware and/or hardware may be modified orappended. Many devices (505), as manufactured, are physically capable ofproviding device-to-device communication, and produce sufficient networkdiagnostic data to participate in an NPS detection network (501B) asdescribed herein. For such devices (505), a simple firmware update, orappropriate programming, is sufficient to configure the device (505) foruse in an NPS detection network (501B).

For example, the network diagnostic features of the devices (505)wireless communication hardware may not be available to ordinaryapplication software without a firmware update. Alternatively, thedevice (505) may need to be “jailbroken” to disable certain security orother protective access-limiting features in order to use the networkdiagnostic data or functionality needed for NPS. For other devices(505), which may lack sufficient inherent functionality to provide theneeded network diagnostic data, the wireless hardware in the device(505) may be replaced or supplemented with additional hardware providingthe required diagnostic data. FIG. 5 depicts one such device (505)modified by additional hardware (601) and/or additional software (603),as needed.

In step (703), the configured user device (505) forms a secondaryfunction network (501B). There are various techniques for performingthis step. By way of example and not limitation, the user device (505),upon entering the physical range of the primary function network (501A),may initiate communications with other discoverable devices (503 n) anddetermine whether any devices (503 n) on the primary function network(501A) are configured to communicate in a secondary function network(501B).

There are many techniques for doing so which will be familiar to thoseof ordinary skill. By way of example and not limitation, the user device(505) may use a proprietary secondary network protocol to query theother devices (503 n). Devices (503 n) which are configured for NPS onthe secondary function network (501B) will be able to understand andrespond to the query, whereas other devices will not. The devices (503n) that respond may then form (703) a secondary function network (501B),in which the user device (505) and responsive devices provide NPSfunctionality in the secondary function network (501B). In the depictedembodiments of FIGS. 4 and 5, one or more of the smart thermostat(503B), smart receptacle (503C), and smart light controller (503D) maybe discoverable responsive devices (i.e., be configured to communicateusing a secondary function network (501B) providing NPS).

Additionally, each responsive device may in turn operate other deviceswhich may not be discoverable (e.g., not directly part of the primaryfunction network (501A)), and/or which may not be configured tocommunicate in the secondary function network (501B). In the depictedembodiment, for example, a sensor (503E) is configured to communicatewith the smart thermostat (503B) using an application- orecosystem-specific protocol, but not necessarily to communicate directlyvia the primary (501A) and/or secondary function networks (501B). Theassociated responsive device (e.g., the smart thermostat) may then makeavailable via the secondary function network (501B) the features,functions, and capabilities of the non-responsive devices.

Alternatively, the user device (505) may join (703) an existingsecondary function network (501B). In a still further embodiment, athird-party service may be used to trigger the activation of the device(505) for use within the secondary function network (501B). As will beunderstood by one of ordinary skill in the art, the particularimplementation of any of these techniques depends upon the networkcommunication protocol used, and the programming of the user device(505) in question, as well as the hardware and firmware of the availabledevices (503 n).

Once the configured device (505) has formed (or joined (703)) thesecondary function network (501B), the user device (505) effectivelybecomes a node (501B) in the network and provides NPS functionality asdescribed in the referenced disclosures above. By way of a simple andnon-limiting example, the user device (505) may establish a baseline ofwireless network communication characteristics with the devices (503 n),or with other user devices (not depicted) within the detection network(501B), and begin to provide NPS functionality by a server (504)observing differences between sets of wireless signal characteristicdata (511) provided to the server (504) as described in the referencesindicated above.

Similarly, the presence of a human, or even a particular user (502), maybe inferred, as described in the above-indicated references, via thepresence of the device (505). A particular user (502) may be inferred tobe present by reference to a user account associated with the userdevice (505). That is, once the user (502) registers the user device(505) to participate in an NPS system, the presence of the registereduser device (505) within a detection network (501B) may be used to inferthe presence of the specific user (502) associated with thatregistration.

Additionally, because the responsive devices are in communication viathe secondary function network (501B), these devices may coordinate thesharing of services. For example, in the depicted embodiments of FIGS. 4and 5, the smart thermostat (503B) may have access to one or moresensors (503E) or other wireless devices (not depicted) which do notcommunicate over the secondary function network (501B), but which dotransmit (515) wirelessly, and thus could be used to provide additionalNPS functionality as a node. Additionally, the application-levelfunctionality of these devices may be shared with the secondary functionnetwork (501B) via a corresponding responsive device (503B). Asdescribed elsewhere herein, by way of example and not limitation, if asensor (503E) senses a fire or other emergency condition, this may beknown by the responsive device (i.e., the smart thermostat (503B)), andthat alert or data may be broadcast via the secondary function network(501B). Alternatively, this information may be transmitted via theprimary function network (501A), and the secondary function network(501B) may be reserved exclusively for NPS functionality.

Generally, it is preferred that the secondary function network (501B) beused where possible so that in the event that the primary functionnetwork (501A) is unavailable, the NPS and functionality sharingnevertheless operate properly. Also by way of example, and notlimitation, the responsive devices, such as smart thermostat (503B),smart power receptacle (503C), and the smart light controller (503D),can communicate via a secondary function network protocol to share theservices and functions that each separate ecosystem provides.

The process of sharing these functions and data generally comprisesrepackaging application- or ecosystem-specific data into a genericprotocol defined by the designer of the secondary function network(501B). This ensures that all participating responsive devices are ableto send and receive information in a way that will be understood byother participating devices. Generally, this results in eachparticipating device having a second network identifier fortransmissions using the secondary function network (501B), and thedevices may negotiate a protocol for data exchange and networkutilization to reduce collisions. The particulars of how the devicesnegotiate use of the secondary function network (501B) will varydepending upon the nature and needs of each device, as well as theprogramming of the underlying application- or ecosystem-specificfunctions. For example, some devices may require that they broadcastapplication data on a particular frequency. In such cases, those devicesnegotiate with other devices in the secondary function network (501B)for use of the primary function network (501A), or the secondaryfunction network (501B), or both, at a particular frequency or interval.All other devices will then cooperate collaboratively in the negotiationof the use of the bandwidth to ensure that each device is able to carryout its primary function as well as the secondary function.

In the case where the configured device (505) establishes (703) asecondary function network (501B), the device (505) may then withdraw(707) from the network (501B), and hand off the management and operationfunction of the secondary function network (501B) to another device.This other device may be another NPS-ready device (503 n) but ispreferably a centralized server system (504) configured with appropriatesoftware for implementing the functions and operations described herein.

Once the secondary function network (501B) is established, the firstdevice (505) may continue to operate (705) as a node within such asecondary function network (501B), or may be withdrawn (707) from orremoved (707) from the network (501B), and the network managementfunctions are performed instead by a server (504). Such a server (504)may be a local server (504) attached through wired or wirelessconnection directly to the router (503A), or may be a remote serverconnecting to the router (503A) and controlling the devices (503 n) viathe Internet (507).

Additionally, in an embodiment, once a secondary function network (501B)is formed, a device generally is assigned as the operator, manager orcoordinator of the network. Initially, this may be a user device (505)used to form the secondary function network (501B). However, it ispreferred that once the network (501B) is formed, this coordinatingfunction is transferred to another device, preferably a deviceconsistently connected to the network (501B). Because user device (505)is typically a mobile device, such as a smart phone or smart tablet, byits nature it is intended to be carried with the user and willeventually leave the physical transmission range of the network (501B).Thus, it is desirable to transfer this function to a fixed device, suchas a server (504), which generally is not removed from the network(501B). As shown in FIGS. 4 and 5, a server (504) may be a part of thenetwork via connection to a wireless router (503A), or via an Internetconnection (507). Once the management function is established at theserver (504), the user device (505) may depart the network (501B)without impacting the overall operation or coordination of itsfunctions.

It will also be clear to one of ordinary skill in the art that becausethe various devices (503 n) are produced by different manufacturers, andhave different hardware components, the transmission and hardwarecharacteristics of each device (503 n) will differ. For example, thewireless antenna used in a smart thermostat (503B) is likely to be madeby a different manufacturer than the antenna in a smart light controller(503D) or smart power receptacle (503C). Because each antenna will havedifferent power requirements for transmission and receipt of radiosignals, the wireless signal characteristic profiles of each may differsignificantly. For the proper functioning of the secondary functionnetwork (501B), it may be important in certain embodiments that thepower and other transmission characteristics of each hardware device betaken into account in performing the NPS functions, so as to improveoverall accuracy and effectiveness.

In an alternative embodiment, fixed devices (503 n), such as thosedepicted in FIGS. 4 and 5, are not necessary to form or create adetection network (501B). In the depicted embodiment of FIG. 7, ad hocdetection networks (501B) may be formed by a plurality of user devices(505) communicating (511) directly with each other. In such anembodiment, the NPS functionality is provided directly by the pluralityof user devices (505), each of which is functionally a node, similar tothe depicted devices (503 n) in FIGS. 4 and 5. However, rather than thefixed nodes communicating with a server (504), the user devices (505)communicate (511) directly with each other, as well as communicate (509)with the server (504). This communication with the server (504) may bevia a general Internet (507) uplink (509) using wireless Internettechnologies as would be understood by one of ordinary skill in the art.

As with the depicted embodiments of FIGS. 4 and 5, the detection network(501B) may be formed (703) automatically or upon prompting. That is,when at least two devices (505) are within sufficient proximity fordirect device-to-device communication, each user may be automaticallyprompted to join or form a detection network (501B) or the devices (505)may automatically form (703) the network (501B). Similarly, when a thirddevice (505) is within range of an existing ad hoc network (501B), theuser (502) may be prompted to join (703) or the device (505) mayautomatically join (703). The particular behavior depends upon how thespecific network is configured to operate, and optionally uponuser-provided preferences or configuration choices. An NPS system formedvia an ad hoc detection network (501B) as depicted in FIG. 7 otherwiseoperates under similar principles to those set forth in the indicatedreferences above.

These systems and methods have a number of advantages. First, the needfor fixed nodes (503) may be obviated in certain circumstances. Second,the particular configuration or hardware manufacturer of the end userdevices (505) is not the deciding factor as to whether a device mayparticipate in the detection network (501). Any number of devices from amultitude of different manufacturers, including devices which areseparately configured with different primary function network purposes,may all nevertheless be leveraged in a secondary purpose network tofacilitate NPS.

Generally, it is expected that specific programming will be desirablefor specific devices due to differences in baseline signal profiles thateach device will create, depending upon the specific wirelesscommunication hardware included in such a device. For example, awireless smartphone manufactured by a given manufacturer, may use aspecific wireless communication hardware component, which producesbaseline signal profiles that differ significantly from the baselinesignal profile generated by a different wireless communication hardwarecomponent manufacturer. Thus, it is likely that a single genericfirmware update or application programming functionality will not besufficient to implement NPS, but rather, programming specific to eachdevice will be preferable. It is important to understand that becausethe NPS functionality is supplemental to the primary network function ofthe device, the systems and methods described herein allow user devices(505) to simultaneously function according to their original design inprimary networks, as well as in secondary networks as NPS nodes. Thatis, NPS-enabled devices would be able to recognize one another as beingenabled via the hardware, firmware, or other software updates, allowingusers to create ad hoc detection networks, which then enable the NPSfunctionality described in the above-indicated references.

By way of an illustrative, non-limiting example, suppose a plurality ofusers enter a concert hall with NPS-enabled (701) devices. The devices(505) may then form an ad hoc detection network (501B) and begin toprovide NPS functionality. If the manager of the facility is subscribedor otherwise participates in an NPS-enabled facilities managementplatform or system, the detection inputs from the ad hoc network (501B)may be provided to the facility systems to automatically operate them toaccommodate the crowd. For example, the collection of devices (505) inthe concert hall may estimate a number of people present, and providethat information to a facilities automation system, or HVAC system,which may then adjust temperature settings to accommodate the size ofthe crowd. As more people arrive, the devices (505) continue to updatethe facilities system with an estimate of the number of people present,allowing for real time adjustments to the temperature settings toprevent the facility from becoming uncomfortably hot. Further, as morepeople arrive, it is likely that more NPS-enabled devices (505) willjoin the network (501B), which will tend to increase the accuracy of theestimates. An embodiment of a facilities management server is depictedin FIG. 7 as element (506).

Because the “ecosystem” of NPS-enabled devices can be built acrossmultiple differing manufacturers and products, a secondary market inNPS-enabled applications may emerge. For example, in the facilitiesexample involving a concert hall described elsewhere herein, each of theindividual users bringing an NPS-enabled device (505) into the concerthall has a primary network function “ecosystem” with the wirelessservice provider for each individual user's phone. That is, each userhas independently selected the specific end-user device (505) that theuser desires, and the specific wireless carrier that the user prefers,independently of any considerations pertaining to NPS. A secondarysubscription may apply to NPS services for participating users,independently of the primary wireless carrier subscription. In anembodiment, users may be incentivized to participate in NPS by receivinga royalty, a stipend, or other payment or micropayment in connectionwith configuring the user device to participate in the network. Suchusers would participate in a network primarily as data providers, notdata consumers. Subscription fees for access to the NPS-enabledsecondary function network would be paid by subscribers or consumers ofthe resulting data. For example, the end users entering the concert hallmay receive a small stipend or micropayment for participating in thedetection network, and the concert hall building manager will pay asubscription fee for access to the resulting data, and use of that datato control facilities automation systems. The separability of chargingand billing of the primary network framework of each device from thesecondary network framework facilitates a clear separation between theindividual device functionality and the extended functionality of acooperating system of NPS-enabled devices.

Additionally, or alternatively, the systems and methods described hereinmay be used to create a system wherein the NPS-enabled devices form asingle network for joint operation. In such embodiment, theparticipating devices recognize the presence of the NPS-enabled otherdevices and form a single wireless communication network for the purposeof NPS functionality. This single communication network facilitates thecoordination of primary network function communication, while stillfacilitating collaboration for purposes of network present sensing in asecondary network function.

In a further embodiment, applications may be programmed or developed tooperate within the secondary network function system. In such anembodiment, the presence of a detection network (501B) and theparticipating devices (505) would provide access to a basic set of dataand functionality in any instance in which a network (501B) may bedetected or formed (703). In such an embodiment, the devices arestandardized on a common hardware and/or firmware standard, ensuringthat all participating devices have similar baseline profilecharacteristics, and that all participating devices provide ongoingnetwork diagnostic information in connection with the detection network(501B). Because all such participating devices are standardized on ahardware and/or firmware standard, the hardware and/or firmware standardmay be configured to provide enhanced functionality to further improvethe operation and accuracy of the NPS system. Further, by standardizingthe hardware and/or firmware, integration of these features withapplication software may be simplified. As a standard, APIs or SDKs maybe utilized to provide uniform access to the network present sensingfunctionality of the participating devices (505).

The systems and methods described herein may be used to implement any ofthe NPS technologies described in the above-indicated references,including, without limitation, change detection (detecting changes inposition of one or more humans within a detection area), presencedetection (occupancy sensing within a detection area), counting(estimating the number of humans present in a detection area), locating(locating specific individuals within a detection area), and the like.This further includes operating third-party systems at varyingperformance levels according to the particular applicationimplementation. Other features may also be implemented, including,without limitation, a creation of maps of the relative locations ofnodes, and learning which nodes form detection networks. The detectionnetworks may further be associated with given actions by learning whichactions are taken by end users when detection networks are formed. Asdescribed in the above-indicated references, this facilitates automaticdevelopment of relationships among devices (505) and events for a givendetection network.

The present systems and methods extend the capability of NPS to operateacross the commercial boundaries of different manufacturers and wirelesscarriers, as well as device-specific product ecosystems. This allowsdifferent devices to collaborate in a generation of network diagnosticinformation, regardless of whether the disparate manufacturers of thedevices design the devices to operate in this fashion. This in turn maylead to the development of secondary product ecosystems, which provideNPS functionality and enable a larger number of devices to participatein the formation or creation of detection networks. This in turnimproves the usefulness and accuracy of NPS technology, furtherdeveloping the functionality of NPS networks. The systems and methodsalso facilitate simpler integration of NPS technology across commercialboundaries, further enhancing the benefits derived from NPSfunctionality.

While the invention has been disclosed in conjunction with a descriptionof certain embodiments, including those that are currently believed tobe preferred embodiments, the detailed description is intended to beillustrative and should not be understood to limit the scope of thepresent disclosure. As would be understood by one of ordinary skill inthe art, embodiments other than those described in detail herein areencompassed by the present invention. Modifications and variations ofthe described embodiments may be made without departing from the spiritand scope of the invention.

The invention claimed is:
 1. A method for sharing device functionalitycomprising: providing a first wireless network device communicating viaa first wireless network configured for telecommunication; providing asecond wireless network device communicating via a second wirelessnetwork configured for telecommunication; providing a user deviceentering a geographic range of said first wireless network anddiscovering said first wireless network device and said second wirelessnetwork device; said user device forming a third wireless network withsaid first wireless network device and said second wireless networkdevice, said third wireless network indicating a presence of humansproximate to said first wireless network based on interference of humanswith wireless network signals emitted by said first wireless networkdevice and said third wireless network indicating a presence of humansproximate to said second wireless network based on interference ofhumans with wireless network signals emitted by said second wirelessnetwork device.
 2. The method of claim 1, further comprising said firstwireless network device making available to said second wireless networkdevice via said third wireless network at least one proprietary functionof said first wireless network device.